The 11th Workshop on Natural User-generated Text (W-NUT)
From Noisy Text to real-world applications of LLMs
Oct, 2026 — collocated with EMNLP 2026.
The WNUT workshop on language by people. We focus on language as it occurs in the real world, from noisy text to real-world applications of LLMs.
Shared Task
This year, we host MultiLexNorm 2: a shared task on multi-lingual lexical normalization with a focus on non Indo-european languages. After the success of our first MultiLexNorm shared task held in 2021, we have extended our benchmark to more varied languages. More information about MultiLexNorm 2
Important Dates
- Submission Deadline: TBA (anytime on earth; dual-submission allowed)
- ARR Commitment Date: TBA
- Acceptance Notification: TBA
- Camera-Ready Deadline: TBA
- EMNLP 2026 Findings Deadline: TBA
- Workshop Day: TBA
Call for Papers
We seek submissions of long and short papers on
original and unpublished work (same page limit as the EMNLP 2026 main conference). All accepted submissions will be presented as talks and/or posters at the workshop, following the EMNLP 2026 main conference.
We welcome submissions addressing (but not limited to) the following areas:
Classical NLP Tasks on Noisy Text- NLP of noisy text, e.g., POS and NER tagging, parsing
- Text normalization and error correction
- Paraphrase identification and semantic similarity of short text or noisy text
- Extracting user demographics, profiles, and major life events
- Machine translation and multilingual NLP over noisy text
- Information extraction from noisy text and event extraction
- Colloquial language, e.g. idiom detection
- Domain adaptation to user-generated text
- Detecting rumors, contradictory information, sarcasm and humor on social media
- Sentiment analysis
- Temporal aspects of user-generated content (resolving time expressions, concept drift, etc...)
- Representing and mining language variation in user-generated content
- Robustness of LLMs to noisy, ungrammatical, or informal input
- Training and fine-tuning of LLMs on user-generated text
- Evaluation methodologies for LLMs on noisy text
- Domain adaptation of LLMs to specific user-generated text domains
- LLM-generated noisy text: detection, characteristics, and implications
- Instruction-following in LLMs when faced with noisy or ambiguous prompts
- Retrieval-augmented generation (RAG) with noisy documents
- LLM performance on text from social media, forums, and messaging platforms
- Handling code-switching, slang, and emerging language in LLMs
- LLMs for content moderation and safety in user-generated contexts
- Multilingual and cross-lingual LLM applications on informal text
- LLMs for assisting language learners and processing learner text
- Bias, fairness, and representation in LLMs trained on user-generated text
We particularly encourage submissions that address multilingual challenges, low-resource languages, cross-platform variations, and the unique characteristics of user-generated text across different communities.
Submissions should conform to the ACL style guidelines. Long and short paper submissions must be anonymized. Please submit your papers via OpenReview or commit them via ARR.
Double Submission Policy: Papers that have been or will be submitted to other meetings or publications must indicate at submission time. Authors of a paper accepted for presentation must notify the workshop organizers by the camera-ready deadline as to whether the paper will be presented or withdrawn.
Workshop Programme
Timezone: CETOrganizers
 |
 |
 |
 |
 |
 |
 |
| JinYeong Bak Associate Professor SungKyunKwan University |
Rob van der Goot Associate Professor IT University of Copenhagen |
Hyeju Jang Assistant Professor Indiana University Indianapolis |
Weerayut Buaphet Ph.D. Student Vidyasirimedhi Institute of Science and Technology |
Alan Ramponi Senior Researcher Fondazione Bruno Kessler |
Wei Xu Associate Professor Georgia Institute of Technology |
Alan Ritter Associate Professor Georgia Institute of Technology |
Contact
jy.bak@skku.eduACL Anti-harassment Policy